Exact and heuristic algorithms for the aerial refueling parallel machine scheduling problem with due date-to-deadline window and ready times

► We model the ARSP as a parallel machine scheduling with ready times and time window. ► We formulated a MIP model and develop two heuristics, MATC and SA to minimize TWT. ► Algorithms are tested in terms of solution quality and CPU time. ► MATC is more likely to outperform SA when the problem size...

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Veröffentlicht in:Computers & industrial engineering 2012-02, Vol.62 (1), p.276-285
Hauptverfasser: Kaplan, Sezgin, Rabadi, Ghaith
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description ► We model the ARSP as a parallel machine scheduling with ready times and time window. ► We formulated a MIP model and develop two heuristics, MATC and SA to minimize TWT. ► Algorithms are tested in terms of solution quality and CPU time. ► MATC is more likely to outperform SA when the problem size increases. ► CPU time performance of MATC is significantly better than SA in both cases. The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for fighter aircrafts (jobs) on multiple tankers (machines) to minimize the total weighted tardiness. ARSP can be modeled as a parallel machine scheduling with ready times and due date-to-deadline window to minimize total weighted tardiness. ARSP assumes that the jobs have different ready times and a due date-to-deadline window between refueling due date and a deadline to return without refueling. In this paper, we first formulate the ARSP as a mixed integer programming model. The objective function is a piece-wise tardiness cost that takes into account due date-to-deadline windows and job priorities. Since ARSP is NP-hard, two heuristics are proposed to obtain solutions in reasonable computation times, namely (1) modified ATC rule (MATC), (2) a simulated annealing method (SA). The proposed heuristic algorithms are tested in terms of solution quality and CPU time through computational experiments with data randomly generated to represent aerial refueling operations of an in-theater air operation. Solutions provided by both algorithms were compared to optimal solutions for problems with up to 12 jobs and to each other for larger problems with up to 60 jobs. The results show that, MATC is more likely to outperform SA especially when the problem size increases, although it has significantly worse performance than SA in terms of deviation from optimal solution for small size problems. Moreover CPU time performance of MATC is significantly better than SA in both cases.
doi_str_mv 10.1016/j.cie.2011.09.015
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subjects Aerial refueling
Algorithms
Central processing units
Computation
Dispatching rule
Due date-to-deadline window
Heuristic
Heuristic methods
Integer programming
Job shops
Mathematical models
Military aircraft
Optimization
Optimization algorithms
Parallel machine scheduling
Production scheduling
Ready time
Refueling
Scheduling
Simulated annealing
Studies
Total weighted tardiness
title Exact and heuristic algorithms for the aerial refueling parallel machine scheduling problem with due date-to-deadline window and ready times
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